Thursday, October 6, 2016

This may be a stereotype, but the Germans are a precise people and while that precision often gets in the way of more creative pursuits (like cooking and valuation), it lends itself well to engineering and banking. For decades until the introduction of the Euro and the creation of the European Central Bank, there was no central bank in the world that matched the Bundesbank for solidity and reliability. Thus, investors and regulators around the world, I am sure, are looking at the travails of Deutsche Bank in the last few weeksand wondering how the world got turned upside down. I am sure that there are quite a few institutions in Greece, Spain, Portugal and Italy who are secretly enjoying watching a German entity be at the center of a market crisis. Talk about schadenfreude!

Deutsche Bank's Journey to Banking Hell

There are others who have told the story about how Deutsche Bank got into the troubles it is in, much more creatively and more fully than I will be able to do so. Consequently, I will stick with the numbers and start by tracing Deutsche Bank’s net income over the last 28 years, in conjunction with the return on equity generated each year.

If Deutsche Bank was reluctant to follow more daring competitors into risky businesses for much of the last century, it threw caution to the winds in the early part of the last decade, as it grew its investment banking and trading businesses and was rewarded handsomely with higher earnings from 2000 to 2007. Like almost every other bank on earth, the crisis in 2008 had a devastating impact on earnings at Deutsche, but the bank seemed to be on a recovery path in 2009, before it relapsed. Some of its recent problems reflect Deutsche’s well chronicled pain in investment banking, some come from its exposure to the EU problem zone (Greece, Spain, Portugal) and some from slow growth in the European economy. Whatever the reasons, in 2014 and 2015, Deutsche reported cumulative losses of close to $16 billion, leading to a management change, with a promise that things would turn around under new management. The other dimension where this crisis unfolded was in Deutsche’s regulatory capital, and as that number dropped in 2015, Deutsche Bank's troubles moved front and center. This is best seen in the graph below of regulatory capital (Tier 1 Capital) from 1998 to 2015, with the ratio of the Tier 1 capital to risk adjusted assets each year super imposed on the graph.

The ratio of regulatory capital to risk adjusted assets at the end of 2015 was 14.65%, lower than it was in 2014, but much higher than capital ratios in the pre-2008 time-period. That said, with the tightening of regulatory capital constraints after the crisis, Deutsche was already viewed as being under-capitalized in late 2015, relative to other large banks early this year. The tipping point for the current crisis came from the decision by the US Department of Justice to levy a $14 billion fine on Deutsche Bank for transgressions related to the pricing of mortgage backed securities a decade ago. As rumors swirled in the last few weeks, Deutsche Bank found itself in the midst of a storm, since the perception that a bank is in trouble often precipitates more trouble, as rumors replace facts and regulators panic. The market has, not surprisingly, reacted to these stories by marking up the default risk in the bank and marking down the stock price, most strikingly over the last two weeks, but also over a much longer period.

At close of trading on October 4, 2016, the stock was trading at $13.33 as share, yielding a market capitalization of $17.99 billion, down more than 80% from its pre-2008 levels and 50% from 2012 levels. Reflecting more immediate fears of default, the Deutsche CDS and CoCo bonds also have dropped in price, and not surprisingly, hedge funds sensing weakness have moved in to short the stock.

Revaluing Deutsche Bank

When a stock is down more than 50% over a year, as Deutsche is, it is often irresistible to many contrarian investors, but knee jerk contrarian investing, i.e., investing in a stock just because it has dropped a lot, is a dangerous strategy. While it is true that Deutsche Banks has lost a large portion of its market capitalization in the last five years, it is also true that the fundamentals for the company have deteriorated, with lower earnings and hits to regulatory capital. To make an assessment of whether Deutsche is now “cheap”, you have to revalue the company with these new realities built in, to see if the market has over reacted, under reacted or reacted correctly to the news. (I will do the entire valuation in US dollars, simply for convenience, and it is straightforward to redo the entire analysis in Euros, if that is your preferred currency).

a. Profitability

As you can see from the graph of Deutsche’s profits and return on equity, the last twelve months have delivered blow after blow to the company, but that drop has been a long time coming. The bank has had trouble finding a pathway to make sustainable profits, as it is torn between the desire of some at the bank to return to its commercial banking roots and the push by others to explore the more profitable aspects of trading and investment banking. The questions in valuation are not only about whether profits will bounce back but also what they will bounce back to. To make this judgment, I computed the returns on equity of all publicly traded banks globally and the distribution is below:

I will assume that given the headwinds that Deutsche faces, it will not be able to improve its returns on equity to the industry median or even its own cost of equity in the near term. I will target a return on equity of 5.85%, at the 25th percentile of all banks, as Deutsche’s return on equity in year 5, and assume that the bank will be able to claw back to earning its cost of equity of 9.44% (see risk section below) in year 10. The estimated return on equity, with my estimates of common equity each year (see section of regulatory capital) deliver the following projected net income numbers.

Year

Common Equity

ROE

Expected Net Income

Base

$64,609

-13.70%

$(8,851)

1

$71,161

-7.18%

$(5,111)

2

$72,754

-2.84%

$(2,065)

3

$74,372

0.06%

$43

4

$76,017

1.99%

$1,512

5

$77,688

5.85%

$4,545

6

$79,386

6.57%

$5,214

7

$81,111

7.29%

$5,910

8

$82,864

8.00%

$6,632

9

$84,644

8.72%

$7,383

10

$86,453

9.44%

$8,161

Terminal Year

$87,326

9.44%

$8,244

I am assuming that the path back to profitability will be rocky, with losses expected for the next two years, before the company is able to turn its operations around. Note also that these expected losses are in addition to the $10 billion fine that I have estimated for the DOJ.

b. Regulatory Capital

Deutsche Bank’s has seen a drop in it Tier 1 capital ratios over time but it now faces the possibility of being further reduced as Deutsche Bank will have to draw on it to pay the US DOJ government fine. While the DOJ has asserted a fine of $14 billion, Deutsche will negotiate to reduce it to a lower number and it is assessing its expected payment to be closer to $6 billion. I have assumed a total capital drop of $ 10 billion, leaving me with and adjusted regulatory capital of $55.28 billion and a Tier 1 capital ratio of 12.41%. Over the next few years, the bank will come under pressure from both regulators and investors to increase its capitalization, but to what level? To make that judgment, I look at Tier 1 capital ratios across all publicly traded banks globally:

I will assume that Deutsche Bank will try to increase its regulatory capital ratio to the average (13.74%) by next year and then push on towards the 75th percentile value of 15.67%. As the capital ratio grows, the firm will have to increase regulatory capital over the next few years and that can be seen in the table below:

Year

Net Income

Risk-Adjusted Assets

Tier 1 Capital/ Risk Adjusted Assets

Tier 1 Capital

Change in Tier 1 Capital

FCFE = Net Income - Change in Tier 1

Base

$(8,851)

$445,570

12.41%

$55,282

1

$(5,111)

$450,026

13.74%

$61,834

$6,552

$(11,663)

2

$(2,065)

$454,526

13.95%

$63,427

$1,593

$(3,658)

3

$43

$459,071

14.17%

$65,045

$1,619

$(1,576)

4

$1,512

$463,662

14.38%

$66,690

$1,645

$(133)

5

$4,545

$468,299

14.60%

$68,361

$1,671

$2,874

6

$5,214

$472,982

14.81%

$70,059

$1,698

$3,516

7

$5,910

$477,711

15.03%

$71,784

$1,725

$4,185

8

$6,632

$482,488

15.24%

$73,537

$1,753

$4,880

9

$7,383

$487,313

15.46%

$75,317

$1,780

$5,602

10

$8,161

$492,186

15.67%

$77,126

$1,809

$6,352

Terminal Year

$8,244

$497,108

15.67%

$77,897

$771

$7,472

The negative free cash flows to equity in the first three years will have to be covered with new capital that meets the Tier 1 capital criteria. By incorporating these negative free cash flows to equity in my valuation, I am in effect reducing my value per share today for future dilution, a point that I made in a different context when talking about cash burn.

c. Risk

Rather than follow the well-trodden path of using risk free rates, betas and risk premiums, I am going to adopt a short cut that you can think of as a model-agnostic way of computing the cost of equity for a sector. To illustrate the process, consider the median bank in October 2016, trading at a price to book ratio of 1.06 and generating a return on equity of 9.91%. Since the median bank is likely to be mature, I will use a stable growth model to derive its price to book ratio:

Plugging in the median bank’s numbers into this equation and using a nominal growth rate set equal to the risk free rate of 1.60% (in US dollars), I estimate a US $ cost of equity for the median bank to be 9.44% in 2016.

Using the same approach, I arrive at estimates of 7.76% for the banks that are at the 25th percentile of risk and 10.20% for banks at the 75th percentile. In valuing Deutsche Bank, I will start the valuation by assuming that the bank is at the 75th percentile of all banks in terms of risk and give it a cost of equity of 10.20%. As the bank finds its legs on profitability and improves its regulatory capital levels, I will assume that the cost of equity moves to the median of 9.44%.

The Valuation

Starting with net income from part a, adjusting for reinvestment in the form of regulatory capital in part b and adjusting for risk in part c, we obtain the following table of numbers for Deutsche Bank.

Year

FCFE

Terminal Value

Cost of equity

Cumulative Cost of Equity

PV

1

$(11,663)

10.20%

1.1020

$(10,583.40)

2

$(3,658)

10.20%

1.2144

$(3,012.36)

3

$(1,576)

10.20%

1.3383

$(1,177.54)

4

$(133)

10.20%

1.4748

$(90.34)

5

$2,874

10.20%

1.6252

$1,768.16

6

$3,516

10.05%

1.7885

$1,965.99

7

$4,185

9.90%

1.9655

$2,129.10

8

$4,880

9.74%

2.1570

$2,262.34

9

$5,602

9.59%

2.3639

$2,369.91

10

$6,352

$87,317

9.44%

2.5871

$36,206.88

Total value of equity

$31,838.74

Value per share =

$22.97

Note that the big number as the terminal value in year 10 reflects the expectation that Deutsche will grow at the inflation rate (1% in US dollar terms) in perpetuity while earning its cost of equity. Note also that since the cost of equity is expected to change over time, the cumulated cost of equity has to be computed as the discount factor. The discounted present value of the cash flows is $31.84 billion, which when divided by the number of shares (1,386 million) yields a value of $22.97 per share. There is one final adjustment that I will make and it reflects the special peril that banks face, when in crisis mode. There is the possibility that the perception that the bank is in trouble could make it impossible to function normally and that the government will have to step in to bail it out (since the option of letting it default is not on the table). I may be over optimistic but I attach only a 10% chance to this occurring and assume that my equity will be completely wiped out, if it occurs. My adjusted value is:

Expected Value per share = $22.97(.9) + $0.00 (.1) = $20.67

Given my many assumptions, the value per share that I get for Deutsche Bank is $20.67. To illustrate how much the regulatory capital shortfall (and the resulting equity issues/dilution) and overhang of a catastrophic loss affect this value, I have deconstructed the value per share into its constituent effects:

Unadjusted Equity Value =

$33.63

- Dilution Effect from new equity issues

$(10.66)

- Expected cost of equity wipeout

$(2.30)

Value of equity per share today =

$20.67

Note that the dilution effect, captured by taking the present value of the negative FCFE in the first four years, reduces the value of equity by 31.69% and the possibility of a catastrophic loss of equity lowers the value another 6.83%. The entire valuation is pictured below:

I know that you will disagree with some or perhaps all of my assumptions. To accommodate those differences, I have set up my valuation spreadsheet to allow for you to replace my assumptions with yours. If you are so inclined, please do enter your numbers into the shared Google spreadsheet that I have created for this purpose and let's get a crowd valuation going!

Time for action or Excuse for inaction?

At the current stock price of $13.33 (at close of trading on October 4), the stock looks undervalued by about 36%, given my estimated value, and I did buy the stock at the start of trading yesterday. Like everyone else in the market, I am uncertain, but waiting for the uncertainty to resolve itself is not a winning strategy. Either the uncertainty will be resolved (in good or bad ways) and everyone will have clarity on what Deutsche is worth, and the price and value will adjust, or the uncertainty will not resolve itself in the near future and you will be sitting on the side lines. For those of you who have been reading my blog over time, you know that I have played this game before, with mixed results. My bets on JP Morgan (after its massive trading loss in 2012) and Volkswagen (after the emissions scandal) paid off well but my investment in Valeant (after its multiple scandals) has lost me 15% so far (but I am still holding and hoping). I am hoping that my Deutsche Bank investment does better, but I strapped in for a rocky ride!

Sunday, October 2, 2016

Venture capitalists (VCs) don’t value companies, they price them! Before you explode, implode or respond with righteous indignation, this is not a critique of what venture capitalists do, but a recognition of reality. In fact, not only is pricing exactly what you should expect from VCs but it lies at the heart of what separates the elite from the average venture capitalist. I was reminded of this when I read a response from Scott Kupor of Andreessen Horowitz, to a Wall Street Journal article about Andreessen, that suggested that the returns earned by the firm on its funds were not as good as those earned at other elite funds. While Scott’s intent was to show that the Wall Street Journal reporter erred in trusting total returns as a measure of VC performance, I think that he, perhaps unintentionally, opened a Pandora’s box when he talked about how VCs attach numbers to companies and how these numbers get updated, and how we (investors, founders and VCs) should read them, as a consequence.

The WSJ versus the VC: A Recap

Let’s start with the Wall Street Journal article that triggered the Kupor response. With the provocative title of “Andreessen Horowitz’s returns trail venture capital elite”, it had all the ingredients for click bait, since a big name (Andreessen Horowitz) failing (“trail venture capital elite”) is always going to attract attention. I must confess that I fell for the bait and read the article and walked away unimpressed. In effect, Rolfe Winkler, the Journal reporter, took the three VC funds run by Andreessen and computed an IRR based upon the realized and unrealized gains at these funds. I have reproduced his graph below:

While the title of the story is technically correct, I am not sure that there is much of a story here. Even if you take the Journal’s estimates of returns at face value, if I were an investor in any of the three Andreessen funds, I would not be complaining about annual returns of 25%-42%, depending on the fund that I invested in. Arguing that I could have done better by investing in a fund in the top 5% of the VC universe would be the equivalent of claiming that Kevin Durant did not having a good NBA season last year, because Lebron James and Stephen Curry had better seasons.

In the hyper-competitive business of venture capital, though, the article must have drawn blood, since it drew Scott Kupor's attention and a response. Scott focused attention specifically on what he believed was the weakest link in the Journal article, the combining of realized and unrealized gains to estimate an internal rate of return. Unlike investments in public equities, where the unrealized returns are based upon observed market prices for traded stocks and can be converted to realized returns relatively painlessly, Scott noted that unrealized returns at venture capital funds are based upon estimates and that these estimates are themselves based upon opaque VC investments in other companies in the space and not easily monetized. Implicitly, he seemed to be saying that not only are unrealized returns at VC funds subject to estimation error, but also to bias, and should thus be viewed as softer than realized returns. I agree, though I think it is disingenuous to go on to argue that unrealized returns should not be considered when evaluating venture capital performance, since VCs seem to have qualms about using them in sales pitches when they serve their purpose.

The VC Game

The Kupor response has been picked in the VC space, with some commenters augmenting legitimate points about return measurement but many more using the WSJ article to restate their view that non-VC people should stop opining about the VC business, because they don’t understand how it works. Having been on the receiving end of this critique at times in the past, you would think I would know better than to butt in, but I just can’t help myself. I may not be qualified to talk about the inner workings of the venture capital business, but I do believe that I am on firmer ground on the specific topic of how VCs attach numbers to the companies that they invest in.

VCs price businesses, not value them!

I have made the distinction between value and price so many times before that I sound like a broken record, but I will make it again. You can value an asset, based upon its fundamentals (cash flows, growth and risk) or price it, based upon what others are paying for similar assets, and the two can yield different numbers.

In public investing, I have argued that this plays out in whether you choose to play the value game (invest in assets where the price < value and hope that the market corrects) or the pricing game (where you trade assets, buying at a lower price and hoping to sell at a higher). I would be glad to be offered evidence to the contrary but based upon the many VC "valuations" that I have seen, VCs almost always play the pricing game, when attaching numbers to companies, and there are four ways in which they seem to do it:

Recent pricing of the same company: In the most limited version of this game, a prospective or existing investor in a private business looks at what investors in the most recent prior round have priced the company to gauge whether they are getting a reasonable price. Thus, for an Uber, this would imply that a pricing close to the $62.5 billion that the Saudi Sovereign fund priced the company at, when it invested $3.5 billion in June 2016, will become your benchmark for a reasonable price, if you are investing close to that date. The dangers in doing this are numerous and include not only the possibility of a pricing mistake (a new investor who over or under prices the company) spiraling up and down the chain, but also the problems with extrapolating to the value of a company from a VC investment in it.

Pricing of “similar” private companies: In a slightly more expanded version of this process, you would look at what investors are paying for similar companies in the “same space” (with all of the subjective judgments of what comprises “similar” and “same space”), scale this price to revenues, or lacking that, a common metric for that space, and price your company. Staying in the ride sharing space, you could price Lyft, based upon the most recent Uber transaction, by scaling the pricing of the company to its revenues (relative to Uber) or to rides or number of cities served.

Pricing of public companies, with post-value adjustments: In the rare cases where a private business has enough operating substance today, in the form of revenues or even earnings, in a space where there are public companies, you could use the pricing of public companies as your basis for pricing private businesses. Thus, if your private business is in the gaming business and has $100 million in revenues and publicly traded companies in that business trade at 2.5 times revenues, your estimated value would be $250 million. That value, though, assumes that you are liquid (as publicly companies tend to be) and held by investors who can spread their risks (across portfolios). Consequently, a discount for lack of liquidity and perhaps diversification is applied, though the magnitude (20%, 30% or more) is one of the tougher numbers to estimate and justify in practice.

Forward pricing: The problem with young start-ups is that operating metrics (even raw ones like riders, users or downloads) are often either non-existent or too small to be base a pricing. To get numbers of any substance, you often have to forecast out the metrics two, three or five years out and then apply a pricing multiple to these numbers. The forecasted metric can be earnings, or if that still is ephermal, it can be revenues, and the pricing multiple can be obtained not just from private transactions but from the public market (by looking at companies that have gone public). That forward value has to be brought back to today and to do so, venture capitalists use a target rate of return. While this target rate of return plays the same mechanical role that a discount rate in a DCF does, that is where the resemblance ends. Unlike a discount rate, a number designed to incorporate the risk in the expected cash flows for a going concern, a target rate of return incorporates not just conventional going-concern risk but also survival risk (since many young companies don’t make it) and the fear of dilution (a logical consequence of the cash burn at young companies), while also playing role as a negotiating tool. Even the occasional VC intrinsic value (taking the form of a DCF) is a forward pricing in disguise, with the terminal value being estimated using a multiple on that year's earnings or revenues.

At the time of a VC investment, the VC wants to push today’s pricing for the company lower, so that he or she can get a greater share of the equity for a given investment in the company. Subsequent to the investment, the VC will want the pricing to go higher for two reasons. First, it makes the unrealized returns on the VC portfolio a much more attractive number. Second, it also means that any subsequent equity capital raised will dilute the VC’s ownership stake less. If you reading this as a criticism of how venture capitalists attach numbers to companies, you are misreading it because I think that this is exactly what venture capitalists should be doing, given how success is measured in the business. This is a business where success is measured less on the quality of the companies that you build (in terms of the cash flows and profits they generate) and more on the price you paid to get into the business and the price at which you exit this business, with that exit coming from either an IPO or a sale. Consequently, how much you are willing to pay for something becomes a process of judging what you will get when you exit and working backwards.

But Venture Capitalists have a data problem

It is not just venture capitalists who play the pricing game. As I have argued before, most investors in public markets (including many who call themselves value investors) are also in the pricing game, though they use pricing metrics of longer standing (from PE to EV/EBITDA) and have larger samples of public traded firms as comparable firms. The challenges with adapting this pricing game to venture capital investments are primarily statistical:

Small Samples: If your pricing is based upon other private company investments, your sample sizes will tend to be much smaller, if you are a VC than if you a public company investor. Thus, as an investor in a publicly traded oil company, I can draw on 351 publicly traded firms in the US or even the 1029 publicly traded companies globally, when making relative value or pricing judgments. A VC investor pricing a ride sharing company is drawing on a sample of less than ten ride sharing firms globally.

With Infrequent Updating: The small sample problem is exacerbated by the fact that unlike public companies, where trading is frequent and prices get updated for most of the companies in my sample almost continuously, private company transactions are few and far between. In many ways, the VC pricing problem is closer to the real estate pricing than conventional stock pricing, where you have to price a property based upon similar properties that have sold in the recent past.

And Opaque transactions: There is a third problem that makes VC pricing complicated. Unlike public equities, where a share of stock is (for the most part) like any other share of stock and the total market value is the share price times number of shares outstanding, extrapolating from a VC investment for a share in a company to the overall value of equity can be and often is complicated. Why? As I noted in an earlier post on unicorn valuations, the VC investment at each stage of capital-raising is structured differently, with a myriad of options embedded in it, some designed for protection (against dilution and future equity rounds) and some for opportunity (allowing future investments at favorable prices). As I noted in that post, a start-up with a "true" value of $750 million can structure an investment, where the VC pays $50 million (instead of $37.5 million) for 5% of the company, by adding enough optionality to the investment. I may be misreading Scott's section on using option pricing to price VC investments, but if I am reading it right, I think Scott is saying that Andreessen uses option pricing models to clean up for the add-on options in VC investments to get to the fair value. Put differently, Andreessen would put a value of $750 million on this company rather than the $1 billion that you would get from extrapolating from the $50 million for 5%.

I am sure that nothing that I have said here is new to venture capitalists, founders and those close to the VC process, but it is the subtle differences that throw off those whose primary experience is in the public markets. That is one reason that public investors should take the numbers that are often bandied about as valuations of private companies (like Palantir, Uber and Airbnb) with a grain of salt. It is also why I think that public investors like mutual funds and university endowment funds should either tread lightly or not all in the space. Even within the VC business, it is sometimes easy, especially in buoyant times to forget how much the entire pricing edifice rests as much on momentum and mood, as it does on the underlying fundamentals.

With Predictable Consequences

So, let’s see. VCs price companies and that pricing is often based upon really small samples with infrequently updated and tough-to-read data. The consequences are predictable.

The pricing estimates will have more noise (error) attached to them. The pricing that I obtain for Lyft, based upon the pricing of Uber, Didi Chuxing and GrabTaxi, will have a larger band around the estimate and there is a greater chance that I will be wrong.

The pricing will be more subjective, since you have the freedom to choose your comparable firms and often can use discretion to adjust for the infrequent data updating and the complexity of equity investments. While that may seem to just be a restatement of the first critique, there is also a much greater potential for bias to enter into the process. Not surprisingly, therefore, not all VC returns are created equal, especially when it comes to the unrealized portion, with more aggressive VCs reporting “higher” returns than less aggressive VCs. That is perhaps the point being made by Scott about realized versus unrealized returns.

The pricing will lag the market: It is a well-established fact that the capital coming into the VC business ebbs and flows across time, with the number of transactions increasing in up markets and dropping in down markets. When there is a severe correction (say, just after the dot-com bust), transactions can come to a standstill, making repricing difficult, if not impossible. If VCs hold off on full repricing until transactions pick up again, there can be a significant lag between when prices drop at young companies and those price drops getting reflected in returns at VC firms.

There is a price feedback loop: Since VC pricing is based upon small samples with infrequent transactions, it is susceptible to feedback loops, where one badly priced transaction (in either direction) can trigger many more badly priced transactions.

And a time horizon issue: The lack of liquidity and small samples that get in the way of pricing holdings also introduce a constraint into the pricing game. Unlike public market investors, where the pricing game can be played in minutes or even fractions of a minute on liquid stocks, private market pricing requires patience and more of it, the younger a company is. Put differently, winning at the VC pricing game may require that you take a position in a young start up and bide your time until you build it up and find someone who will find it attractive enough to offer you a much higher price for it. This is perhaps what Scott was talking about, in his response, when he talked about this being VC investing being a "long" game.

There is one final point that also needs to be made. Much as we like to talk about the VC market and the public market as separate, populated by different species, they are linked at the hip. To the extent that a venture capitalist has to plot an exit, either in an initial public offering or by selling to a publicity traded company, if the public market catches a cold, the venture capital market will get pneumonia, though the diagnosis may come much later.

The VC Edge

If I were to summarize the entire post in a couple of sentences, here is what it would say. Venture capitalists price the companies they invest in, base that pricing on small samples of opaque transactions and the pricing is therefore more likely to be wrong and lag reality. That sounds pretty damning, but I think that these features work to the advantage of venture capitalists, or at least the very best among them. That may sound contradictory, but here is my basis for making that statement.

The average VC does better than the average public market active investor: Both VC and public market investors play the pricing game, with the latter having the advantage of more and better data, but over time, venture capitalists seem to deliver better results than public market investors, as seen in the graph below. These are raw returns and I do realize that you have to adjust for risk, but some of the biggest risks in venture capital (failure risk) have already been incorporated into long term returns.

The Elite: The most successful VCs not only earn higher returns than the top public market investors but that there seems to be more consistency in the VC business, insofar as the best of the VCs are able to generate higher returns across longer time periods. That would suggest that venture capitalists bring more durable competitive advantages to the investing game than public market investors.

How do I reconcile my argument that the VC pricing game is inherently more error-prone and noisy with the fact that VCs seem to make money at it? I think that the very factors that make it so difficult to price and profit of a VC investment are what allow VCs collectively to earn excess returns and the very best VCs to set themselves apart from the rest. In particular, the best in the business set themselves apart from the rest on three dimensions:

They are better pricers (relatively): As Scott notes in his piece, the price that you can attach to a VC investment can vary widely across investors and he uses the example of how Andreessen's option pricing approach can yield a lower pricing for the same company than an alternative approach. While all of these prices are undoubtedly wrong (because they are estimates), some of them are less wrong than others. Repeating a statement that I have made before, you don't have to be right to make money, you just have to be less wrong than everyone else and the chances of you doing that are greater in the VC pricing game.

They can influence the pricing game: Unlike public market investors, who for the most part can observe company metrics but not change them, venture capitalists can take a more active role in the companies that they invest in, from informally advising managers to more formal roles as board members, helping these companies decide what metrics to focus on, how to improve these metrics and how (and when) to cash in on them (from an IPO or a sale).

They have better timing: The pricing game is all about timing, and the VC pricing game is more emphatically so. To be successful, you not only have to time your entry into a business right but even more critically, time your exit from it.

If you are an investor in a VC fund, therefore, you should of course look at both realized returns and unrealized returns, but you should also look at how the fund measures its unrealized returns and how it has generated its returns. A realized return that comes primarily from one big hit is clearly less indicative of skill than a return that reflects multiple hits over longer time periods. After all, if separating luck from skill is difficult in the public marketplace, it can become even more so in the venture capital business.